Summary
Overview
Work History
Education
Skills
Websites
References
Timeline
Generic

Keith Portman

Mint Hill,NC

Summary

Seasoned machine learning engineer and data scientist looking for the next challenge. I have deep hands-on experience with modern data science and AI technologies, but I am strongly motivated by the commercial application of data science and analytics. I have also managed teams of 8+ individuals from varying technical backgrounds across a variety of functions including marketing, risk, product and strategy. Sophisticated Machine Learning Engineer with background in independent research using intuitive, web-based architecture. Skilled in [Skill] with documented history of discovering methods to intelligently use data to enhance user experience. Effectively researches techniques for novel approaches to problems, develops prototypes to assess viability of approach and deploys application into production yielding insights to expand customer-consciousness.

Overview

13
13
years of professional experience

Work History

Machine Learning Engineer/Consultant

Various Tech Companies
01.2023 - Current
  • Developed data pipelines in AWS to deliver the output of ML models to the end user
  • Created supervised and unsupervised NLP topic models for the classification of chat and survey data
  • Leveraged TensorFlow to create unit and event level outage forecasts using an optimized ANN
  • Coached and mentored junior engineers and data scientists on approaches like topic modeling, classification, and deep learning.

Chief Analytics Officer

Embrace Home Loans - Middletown, RI
10.2019 - 11.2022
  • Built a world class data science practice that leveraged Machine Learning and NLP techniques to drive customer acquisition and retention strategies
  • Partnered with Capital Markets, Operations, and Underwriting to develop use cases for AI to improve customer experience
  • Developed and managed the end-to-end process for building and deploying ML and AI pipelines in Azure to optimize customer response/conversion – Deep Learning, XG Boost, NLP, Random Forests, Lasso regression (Test AUCs as high as 90%)
  • Mentored Data Scientists to leverage AI techniques on text, voice and traditional data sources
  • Drove the marketing targeting strategy that deployed 20M+ touchpoints per year and delivered $45M+ in incremental revenue
  • Stayed up to date on cutting edge techniques in AI and ML and continuously evaluated new technologies.

Director of Data Science

BFS Capital – Coral Springs, FL
10.2018 - 10.2019
  • Provided strategy and direction for AI and ML use cases around development, deployment, and performance validation
  • Developed and managed a high performing data science team consisting of three data scientists and two data engineers
  • Represented the Risk department as a key member of the cross functional leadership team which communicated progress to key stakeholders during AI solution design and implementation
  • Designed and implemented of a proprietary risk-based pricing engine that leveraged traditional and non-traditional data sources typically called through API integrations
  • Developed and implemented cutting edge Machine Learning Classification models in Python including XG Boost, Neural Networks, and Regularized Regression (Test AUC values of 80+%).

Director of Revenue Growth Management

Reynolds American – Winston Salem, NC
08.2015 - 10.2018
  • Developed and deployed state level pricing models across all drive brands for cigarettes and moist that generated an incremental $50M in pricing efficiency
  • Delivered key pricing strategies that were presented to senior management around the ideas of percent price gap needs, assortment optimization, and VAP allocation
  • Provided technical leadership and mentoring to junior data scientists and analytical resources
  • Represented S&P as a core member of the cross functional leadership team that managed the pricing efficiency strategies including the optimization of more than $700M in pricing and promotion for combustibles
  • Developed sales and marketing tools including dashboards and model simulators to estimate the impact of changes in pricing.

Senior Vice President Analytics

Bank of America – Charlotte, NC
03.2014 - 08.2015
  • Managed a matrixed team of eight onsite and offshore data science and analytics resources
  • Developed and implemented a proprietary spend classification process that leveraged ML to re-allocate $200M in spend to the subcategory level across all LOBs
  • Established KPIs and metrics to track the cost savings of the spend re-allocation
  • Developed ML classification tools to identify the riskiest vendors in the portfolio
  • Created custom reporting and dashboards that tracked vendor spend across categories for all of the different LOBs.

Associate Director Data Mining & Analytics

CUNA Mutual Group – Madison, WI
04.2011 - 03.2014
  • Responsible for developing and deploying the entire suite of ML/predictive models within the DTC area
  • New models typically generated $10M-$15M in incremental revenue per year
  • Managed a best-in-class team of five data scientists that provided analytical support in the form of data science, predictive modeling, reporting, and forecasting
  • Developed and deployed a contact optimization strategy across the organization which entailed leading cross-functional teams from marketing, IT, product, and operations resulting in $14M in incremental revenue
  • Initiated the use of boosted trees in our modeling process in place of the traditional logistic models which netted a 10% increase in response rates across all products.

Education

ABD - Applied Mathematics -

University of Notre Dame

Artificial Intelligence Engineer – Master’s Program -

Purdue University/Simplilearn
01.2022

Post Masters in Data Science -

Purdue University/Simplilearn
01.2021

M.S. Computational Finance/Statistics -

Purdue University
01.2004

M.S. Applied Mathematics -

The University of Michigan
01.2001

B.S. Pure Mathematics (Summa Cum Laude) -

Indiana University
01.2000

Skills

  • Executive Skills – Leadership, Strategy and execution, Business development, Communication with influence
  • Team Building – Analytical talent development, technical mentorship, Coaching for professional growth
  • Data Science- Deep Learning, Machine Learning, Natural Language Processing, Time Series Forecasting, Pricing models
  • Data Visualization – Tableau, Power BI, Sigma, Qlik, Excel
  • Programming Languages- Python, R, SQL
  • Machine Learning
  • Machine Learning Integration
  • Data Analytics
  • Project Management
  • Data Mining
  • Model Development

Websites

References

References are available on request.

Timeline

Machine Learning Engineer/Consultant

Various Tech Companies
01.2023 - Current

Chief Analytics Officer

Embrace Home Loans - Middletown, RI
10.2019 - 11.2022

Director of Data Science

BFS Capital – Coral Springs, FL
10.2018 - 10.2019

Director of Revenue Growth Management

Reynolds American – Winston Salem, NC
08.2015 - 10.2018

Senior Vice President Analytics

Bank of America – Charlotte, NC
03.2014 - 08.2015

Associate Director Data Mining & Analytics

CUNA Mutual Group – Madison, WI
04.2011 - 03.2014

ABD - Applied Mathematics -

University of Notre Dame

Artificial Intelligence Engineer – Master’s Program -

Purdue University/Simplilearn

Post Masters in Data Science -

Purdue University/Simplilearn

M.S. Computational Finance/Statistics -

Purdue University

M.S. Applied Mathematics -

The University of Michigan

B.S. Pure Mathematics (Summa Cum Laude) -

Indiana University

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